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Record W2021057208 · doi:10.1109/3.890281

Theory of large-signal direct modulation of extended cavity semiconductor lasers with dispersive loss

2000· article· en· W2021057208 on OpenAlexaff
Lora Ramunno, J. E. Sipe

Bibliographic record

VenueIEEE Journal of Quantum Electronics · 2000
Typearticle
Languageen
FieldEngineering
TopicSemiconductor Lasers and Optical Devices
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsChirpSemiconductor laser theoryPhysicsOpticsModulation (music)Adiabatic processIntensity modulationLaserDispersion (optics)Laser diode rate equationsFrequency modulationDiodeSIGNAL (programming language)OptoelectronicsMaterials sciencePhase modulationInjection seederTelecommunicationsQuantum mechanicsRadio frequencyAcousticsComputer science

Abstract

fetched live from OpenAlex

We present a model of coupled semiconductor diode-dispersive extended cavity lasers that describes arbitrarily large current modulation, does not assume uniform photon and carrier densities within the semiconductor diode gain medium, and is simple to implement numerically. In particular, we look at the fiber grating laser, an example of such a coupled system that has been studied as a possible optical communications source. We find simple expressions for the instantaneous frequency and intensity in terms of a few parameters characterizing the dispersion, allowing for the design of the system to minimize chirp. From these expressions we also recover Kazarinov and Henry's adiabatic chirp formula in the limit of slow modulation and Petermann's dynamical chirp formula in the limit of uniform carrier and photon densities. We show that in typical cases, where nonuniformity is important, the instantaneous frequency modulation is quantitatively and qualitatively different than is predicted by previous models.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.008
GPT teacher head0.222
Teacher spread0.213 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations3
Published2000
Admission routes1
Has abstractyes

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